AI-based Green Video Coding

About the project or challenge area

The use of streaming video has increased exponentially in recent years, which is associated with significant energy consumption and carbon emissions from display devices, network infrastructure and data centres. In this project, we will investigate the climate impact of video compression, which is the key technique for video communication. Based on our recent works on deep learning based video compression, we will use AI-based approaches to enhance conventional video coding methods, achieving both lower overall computational complexity and improved coding performance. This work will offer new solutions to reduce the climate impact of video streaming without comprising (actually with improved) user experience.

Why choose this opportunity?

In this project, you will have the opportunity to conduct cutting-edge research work on AI-based video compression using the advanced deep learning workstations in the VI-Lab. You will also work alongside senior PhD students and Post-doc researchers within Bristol Vision Institute and the new MyWorld programme.

About you

Advanced programming skills using Matlab/C++/Python will be desirable.

How to apply

All students can apply using the button below, following the Cabot Masters by Research Admission Statement. Please note that this is an advertised project, which means you only have to complete Section A of the Research Statement.

Before applying, we recommend getting in touch with the project's supervisors. If you are interested in this project and would like to learn more about the research you will be undertaking, please use the contact details on this page.

Research Fellow, Department of Electrical & Electronic Engineering Supervisor

Your supervisor for this project will be Dr Fan (Aaron) ZhangResearch FellowDepartment of Electrical & Electronic Engineering

You can email him at:

Visual Information Laboratory, Department of Electrical & Electronic Engineering

Your co-supervisor for this project will be Professor David R Bull in the Department of Electrical & Electronic Engineering You can email him at

Find out more about your prospective research community

The Low Carbon Energy theme is a vibrant community of researchers who innovate in every part of the energy system, from generation and storage, to regulation and end-user demand. Find out more about the Low Carbon Energy research theme.
Edit this page